scholarly journals A Real Estate Valuation Model using Boosted Feature Selection

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Kankawee Chanasit ◽  
Ekapol Chuangsuwanich ◽  
Atiwong Suchato ◽  
Proadpran Punyabukkana
2014 ◽  
Vol 12 (3) ◽  
pp. 65-73
Author(s):  
Seung-Hwan Ku ◽  
Wang-Ping ◽  
Jang Seong Yong ◽  
김두석

2021 ◽  
Vol 4 ◽  
pp. 5-26
Author(s):  
Janek Ratnatunga ◽  

There are numerous financial metrics available in the academic and commercial world to estimate real estate value. Appraisers often use such metrics when advising on the purchase or sale of real estate at a point in time. The first part of this paper proposes a new metric, based on the capability approach, to make an ex-post single period valuation. Further, appraisers often give advice to their clients on actions to take in order to enhance the value of their real estate. This area of value enhancement has received scant attention in the academic literature. In practice, this advice is often based ad-hoc, anecdotal recommendations. The second part of the paper develops seven real estate strengths that can be targeted and provides an ex-ante approach to building real estate value. The valuation model presented in this paper is a pragmatic approach to enhancing both the values of tangible and intangible capabilities of a property by utilizing Expense Leveraged Value Indexes (ELVI).


2014 ◽  
Vol 12 (3) ◽  
pp. 65-73
Author(s):  
Seung-Hwan Gu ◽  
◽  
Doo-Suk Kim ◽  
Wang Ping ◽  
Seong-Yong Jang

2019 ◽  
Vol 23 (3) ◽  
pp. 197-212 ◽  
Author(s):  
Fatma Bunyan Unel ◽  
Sukran Yalpir

Predicting the value of real estate is a complex endeavor due to the abundance of subjective criteria. Objective consideration of the value-affecting criteria in real estate and regulation of decision support systems will enable the acquisition of more accurate results. In this study, analytic hierarchy process (AHP), a type of multi-criteria decision analysis (MCDA), is used to reproduce coefficients that serve as the basis for real estate valuation. A region in the Selcuklu district of Konya, Turkey was used to test the model created by AHP. Weighted criteria describing areas subjected to purchase/sale were generated by the AHP method and then validated. Additionally, a valuation model was created by the multiple regression analysis (MRA) method for comparison and performance analyses. Weighted values were transformed from AHP points and acquired from the MRA method and then joined with geographic information systems (GIS). Value maps of the study area and purchase/sale values were generated according to these newly created models. The performance comparison and value maps revealed that the AHP method is more successful than the MRA method. This study addressed the complexity of criteria issue by using the original hierarchical structure of AHP and thus contributes to the world economy by enabling the generation of more accurate estimations.


2021 ◽  
Vol 108 ◽  
pp. 105539
Author(s):  
Sukran Yalpir ◽  
Suleyman Sisman ◽  
Ali Utku Akar ◽  
Fatma Bunyan Unel

2015 ◽  
Author(s):  
Mehmet Levent ◽  
Semih Adil ◽  
Ayse Gokbayrak

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